Search (1 results, page 1 of 1)

  • × author_ss:"Borsack, J."
  • × author_ss:"Tagheva, K."
  1. Tagheva, K.; Borsack, J.; Condit, A.: Effects of OCR errors on ranking and feedback using the vector space model (1996) 0.00 
    0.0023435948 = product of:
  0.0046871896 = sum of:
    0.0046871896 = product of:
      0.009374379 = sum of:
        0.009374379 = weight(_text_:a in 4951) [ClassicSimilarity], result of:
          0.009374379 = score(doc=4951,freq=6.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.17652355 = fieldWeight in 4951, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0625 = fieldNorm(doc=4951)
      0.5 = coord(1/2)
  0.5 = coord(1/2)
    Abstract
    Reports on the performance of the vector space model in the presence of optical character recognition (OCR) errors. Average precision and recall is not affected for full text document rankings of the OCR and corrected collections with different weithing combinations. Cosine normalization plays a considerable role in the disparity seen between the collections. Even though feedback improves retrieval for both collections, it can not be used to compensate for OCR errors caused by badly degraded documents
    Type
    a